Changes in the latencies of visual-evoked potentials in people undergoing tennis training Dynamic comparison before and after 8 weeks training

BACKGROUND： Some previous studies have shown that exercise is an important factor that affects the latencies of visual-evoked potentials （VEPs）. OBJECTIVE： To investigate the effects of spending a period of time undergoing tennis training on the latencies of VEPs by comparing the latencies of VEPs before tennis training with those after 8 weeks of tennis training. DESIGN, TIME AND SETTING： The non-randomly concurrent controlled experiment was performed in the Department of Human Movement Sciences, Physical Education College, Shandong Normal University from April to June 2007. PARTICIPANTS： In total, 45 healthy volunteers from Shandong Normal University were selected as subjects, including 31 students majoring in physical education （11 males and 5 females participated in the tennis training plan for 8 weeks）, and 14 students from other subjects. Informed consent was obtained. According to whether they were majoring in physical education or not, and whether or not they took part in tennis training, the students were divided into 3 groups： a tennis group of physical education students （n = 16） a non-tennis group of physical education students （n =15） and a non-tennis group of non-physical education students （n = 14）. METHODS： The subjects in the tennis group took part in a regular tennis training plan of 2 hours a day and 3 days per week, for 8 weeks, while the subjects in two non-tennis groups were not in the tennis training plan The NDI-200 neural electricity tester （Shanghai Haishen Medical Electronic Instrument Co., Ltd.） was used to measure VEPs before and after the experiment in all three groups, and to compare the latencies of VEPs recorded before training with those recorded after training. MAIN OUTCOME MEASURES： Comparison of the changes in latencies of VEPs before and after 8 weeks of tennis training. RESULTS： All 45 subjects finished the test and datas from all were included in the statistical analysis. There were no significant differences among all the three groups before tennis training, but the female subjects in each group showed significantly shorter N75 latencies than male subjects of the same group （P 〈 0.05）. Comparing the latencies of VEPs after training with those recorded before training, the N75, P100 and N145 latencies were all found to be significantly shorter than before training in the tennis group （P 〈 0.05）, but the N75, P100 and N145 latencies were unaffected in the two non-tennis groups （P 〉 0.05）; some latencies were even significantly longer than the before-training values. CONCLUSION： Special tennis training for 8 weeks can make the subjects＇ VEP latencies significantly shorter. Thus, VEP latencies can change with tennis training.

Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

Efficient Digital Twin Placement for Blockchain-Empowered Wireless Computing Power Network

As an open network architecture,Wireless Computing PowerNetworks(WCPN)pose newchallenges for achieving efficient and secure resource management in networks,because of issues such as insecure communication channels and untrusted device terminals.Blockchain,as a shared,immutable distributed ledger,provides a secure resource management solution for WCPN.However,integrating blockchain into WCPN faces challenges like device heterogeneity,monitoring communication states,and dynamic network nature.Whereas Digital Twins(DT)can accurately maintain digital models of physical entities through real-time data updates and self-learning,enabling continuous optimization of WCPN,improving synchronization performance,ensuring real-time accuracy,and supporting smooth operation of WCPN services.In this paper,we propose a DT for blockchain-empowered WCPN architecture that guarantees real-time data transmission between physical entities and digital models.We adopt an enumeration-based optimal placement algorithm(EOPA)and an improved simulated annealing-based near-optimal placement algorithm(ISAPA)to achieve minimum average DT synchronization latency under the constraint of DT error.Numerical results show that the proposed solution in this paper outperforms benchmarks in terms of average synchronization latency.

Multi-network-region traffic cooperative scheduling in large-scale LEO satellite networks

A low-Earth-orbit(LEO)satellite network can provide full-coverage access services worldwide and is an essential candidate for future 6G networking.However,the large variability of the geographic distribution of the Earth’s population leads to an uneven service volume distribution of access service.Moreover,the limitations on the resources of satellites are far from being able to serve the traffic in hotspot areas.To enhance the forwarding capability of satellite networks,we first assess how hotspot areas under different load cases and spatial scales significantly affect the network throughput of an LEO satellite network overall.Then,we propose a multi-region cooperative traffic scheduling algorithm.The algorithm migrates low-grade traffic from hotspot areas to coldspot areas for forwarding,significantly increasing the overall throughput of the satellite network while sacrificing some latency of end-to-end forwarding.This algorithm can utilize all the global satellite resources and improve the utilization of network resources.We model the cooperative multi-region scheduling of large-scale LEO satellites.Based on the model,we build a system testbed using OMNET++to compare the proposed method with existing techniques.The simulations show that our proposed method can reduce the packet loss probability by 30%and improve the resource utilization ratio by 3.69%.

Examining the Quality Metrics of a Communication Network with Distributed Software-Defined Networking Architecture

Software-Defined Networking(SDN),with segregated data and control planes,provides faster data routing,stability,and enhanced quality metrics,such as throughput(Th),maximum available bandwidth(Bd(max)),data transfer(DTransfer),and reduction in end-to-end delay(D(E-E)).This paper explores the critical work of deploying SDN in large-scale Data Center Networks(DCNs)to enhance its Quality of Service(QoS)parameters,using logically distributed control configurations.There is a noticeable increase in Delay(E-E)when adopting SDN with a unified(single)control structure in big DCNs to handle Hypertext Transfer Protocol(HTTP)requests causing a reduction in network quality parameters(Bd(max),Th,DTransfer,D(E-E),etc.).This article examines the network performance in terms of quality matrices(bandwidth,throughput,data transfer,etc.),by establishing a large-scale SDN-based virtual network in the Mininet environment.The SDN network is simulated in three stages:(1)An SDN network with unitary controller-POX to manage the data traffic flow of the network without the server load management algorithm.(2)An SDN network with only one controller to manage the data traffic flow of the network with a server load management algorithm.(3)Deployment of SDN in proposed control arrangement(logically distributed controlled framework)with multiple controllers managing data traffic flow under the proposed Intelligent Sensing Server Load Management(ISSLM)algorithm.As a result of this approach,the network quality parameters in large-scale networks are enhanced.

Advancing the predictive accuracy of PNTML in rectal prolapse:An ongoing quest

Fecal incontinence is a common symptom among patients with rectal prolapse.Pudendal nerve terminal motor latency(PNTML)testing can serve as a reference indicator for predicting the outcomes of rectal prolapse surgery,thereby assisting surgeons in formulating more appropriate surgical plans.The direct correlation between preoperative PNTML testing results and postoperative fecal incontinence in patients with rectal prolapse remains a contentious issue,necessitating further clarification.Thus,we analyze the existing publications from both clinical and statistical perspectives to comprehensively evaluate the accuracy of preoperative PNTML testing in rectal prolapse and provide some feasible statistical solutions.

Energy Minimization for Heterogenous Traffic Coexistence with Puncturing in Mobile Edge Computing-Based Industrial Internet of Things

Puncturing has been recognized as a promising technology to cope with the coexistence problem of enhanced mobile broadband(eMBB) and ultra-reliable low latency communications(URLLC)traffic. However, the steady performance of eMBB traffic while meeting the requirements of URLLC traffic with puncturing is a major challenge in some realistic scenarios. In this paper, we pay attention to the timely and energy-efficient processing for eMBB traffic in the industrial Internet of Things(IIoT), where mobile edge computing(MEC) is employed for data processing. Specifically, the performance of eMBB traffic and URLLC traffic in a MEC-based IIoT system is ensured by setting the threshold of tolerable delay and outage probability, respectively. Furthermore,considering the limited energy supply, an energy minimization problem of eMBB device is formulated under the above constraints, by jointly optimizing the resource blocks(RBs) punctured by URLLC traffic, data offloading and transmit power of eMBB device. With Markov's inequality, the problem is reformulated by transforming the probabilistic outage constraint into a deterministic constraint. Meanwhile, an iterative energy minimization algorithm(IEMA) is proposed.Simulation results demonstrate that our algorithm has a significant reduction in the energy consumption for eMBB device and achieves a better overall effect compared to several benchmarks.

Comparative Performance Measurement of the Pareto Optimal Combination and Multi-Objective Combination Models for Controller Placement in Software-Defined Networks

The evolution of the current network has challenges of programmability, maintainability and manageability, due to network ossification. This challenge led to the concept of software-defined networking (SDN), to decouple the control system from the infrastructure plane caused by ossification. The innovation created a problem with controller placement. That is how to effectively place controllers within a network topology to manage the network of data plane devices from the control plane. The study was designed to empirically evaluate and compare the functionalities of two controller placement algorithms: the POCO and MOCO. The methodology adopted in the study is the explorative and comparative investigation techniques. The study evaluated the performances of the Pareto optimal combination (POCO) and multi-objective combination (MOCO) algorithms in relation to calibrated positions of the controller within a software-defined network. The network environment and measurement metrics were held constant for both the POCO and MOCO models during the evaluation. The strengths and weaknesses of the POCO and MOCO models were justified. The results showed that the latencies of the two algorithms in relation to the GoodNet network are 3100 ms and 2500 ms for POCO and MOCO respectively. In Switch to Controller Average Case latency, the performance gives 2598 ms and 2769 ms for POCO and MOCO respectively. In Worst Case Switch to Controller latency, the performance shows 2776 ms and 2987 ms for POCO and MOCO respectively. The latencies of the two algorithms evaluated in relation to the Savvis network, compared as follows: 2912 ms and 2784 ms for POCO and MOCO respectively in Switch to Controller Average Case latency, 3129 ms and 3017 ms for POCO and MOCO respectively in Worst Case Switch to Controller latency, 2789 ms and 2693 ms for POCO and MOCO respectively in Average Case Controller to Controller latency, and 2873 ms and 2756 ms for POCO and MOCO in Worst Case Switch to Controller latency respectively. The latencies of the two algorithms evaluated in relation to the AARNet, network compared as follows: 2473 ms and 2129 ms for POCO and MOCO respectively, in Switch to Controller Average Case latency, 2198 ms and 2268 ms for POCO and MOCO respectively, in Worst Case Switch to Controller latency, 2598 ms and 2471 ms for POCO and MOCO respectively, in Average Case Controller to Controller latency, 2689 ms and 2814 ms for POCO and MOCO respectively Worst Case Controller to Controller latency. The Average Case and Worst-Case latencies for Switch to Controller and Controller to Controller are minimal, and favourable to the POCO model as against the MOCO model when evaluated in the Goodnet, Savvis, and the Aanet networks. This simply indicates that the POCO model has a speed advantage as against the MOCO model, which appears to be more resilient than the POCO model.

An Emergency Plan Selection Method for Emergency Latency

Drawing upon a characteristic analysis of the latency period in emergencies,this paper proposes an emergency plan selection method based on interval language variables and information entropy to address the challenge of acquiring critical information during this crucial stage.Initially,decision-makers employ interval language variables to express the preference information regarding emergency plans,while also introducing an enhanced information entropy theory to derive the weight coefficients of key indicators.Subsequently,the weighted arithmetic average operator of interval language is applied twice to aggregate the preference information alongside the relative importance of decision-makers and the weight coefficients of key indicators.Finally,the ranking coefficients of each emergency plan are sorted to determine the optimal scheme.The feasibility and effectiveness of this method are demonstrated through a case study involving the selection of an emergency plan for a flood disaster in a specific location.

Formulating and Supporting a Hypothesis to Address a Catch-22 Situation in 6G Communication Networks

2030 is projected as the year for the launch of the 6G (sixth generation) telecommunication technology. It is also the year predicted to introduce quantum computers powerful enough to break current cryptography algorithms. Cryptography remains the mainstay of securing the Internet and the 6G networks. Post quantum cryptography (PQC) algorithms are currently under development and standardization by the NIST (National Institute of Standards and Technology) and other regulatory agencies. PQC deployment will make the 6G goals of very low latency and low cost almost unachievable, as most PQC algorithms rely on keys much larger than those in classical RSA (Rivest, Shamir, and Adleman) algorithms. The large PQC keys consume more storage space and processing power, increasing the latency and costs of their implementation. Thus, PQC deployment may compromise the latency and pricing goals of 6G networks. Moreover, all the PQC candidates under NIST evaluation have so far failed, seriously jeopardizing their standardization and placing the security of 6G against the Q-Day threat in a catch-22 situation. This report formulates a research question and builds and supports a research hypothesis to explore an alternate absolute zero trust (AZT) security strategy for securing 6G networks. AZT is autonomous, fast, and low-cost.

Quantum-Edge Cloud Computing for IoT: Bridging the Gap between Cloud, Edge, and Quantum Technologies

The rapid expansion of the Internet of Things (IoT) has driven the need for advanced computational frameworks capable of handling the complex data processing and security challenges that modern IoT applications demand. However, traditional cloud computing frameworks face significant latency, scalability, and security issues. Quantum-Edge Cloud Computing (QECC) offers an innovative solution by integrating the computational power of quantum computing with the low-latency advantages of edge computing and the scalability of cloud computing resources. This study is grounded in an extensive literature review, performance improvements, and metrics data from Bangladesh, focusing on smart city infrastructure, healthcare monitoring, and the industrial IoT sector. The discussion covers vital elements, including integrating quantum cryptography to enhance data security, the critical role of edge computing in reducing response times, and cloud computing’s ability to support large-scale IoT networks with its extensive resources. Through case studies such as the application of quantum sensors in autonomous vehicles, the practical impact of QECC is demonstrated. Additionally, the paper outlines future research opportunities, including developing quantum-resistant encryption techniques and optimizing quantum algorithms for edge computing. The convergence of these technologies in QECC has the potential to overcome the current limitations of IoT frameworks, setting a new standard for future IoT applications.

软件流水中隐藏存储延迟的方法

软件流水是一种重要的指令调度技术,它通过同时执行来自不同循环体的指令来加快循环的执行速度.随着处理机运行速度的逐渐提高,存储访问延迟成为性能提高的瓶颈.为了减轻存储系统影响,软件流水结合了一些存储优化技术,通过隐藏存储延迟来提高性能.提出了一种延迟可预测的模调度算法(foresightedlatencymoduloscheduling,简称FLMS),它根据循环的特点来确定load指令延迟.实验结果表明,FLMS算法减少了阻塞时间,提高了程序性能.

中国抗精神病药物治疗精神分裂症患者P300潜伏期和波幅变化的Meta分析(英文)

背景事件相关电位研究表明,精神分裂症患者的认知功能损害与P300的潜伏期和波幅有关,但尚不清楚这些认知功能的改变是否会随着药物治疗而改变。目的汇集中国的随访研究,确定抗精神病药物治疗与P300成分改变的关系。方法手工和电子检索1982年1月至2011年12月在中国进行的、以中文或英文发表的文献,内容为抗精神病药物治疗前后精神分裂症患者P300的潜伏期和波幅变化。2位评定者对12项符合Meta分析纳入标准的研究独立进行分析。12项研究中有17个样本的P300波幅峰值具有同质性,因而采用固定效应模型计算汇集的标准化效应值(pooledstandardized effect size,PSES);但P300潜伏期数值具有异质性,因而采用随机效应模型计算PSES。采用Egger's和Begg's检验及倒漏斗图分析发表性偏倚。结果汇集样本的611例受试者中,治疗前后完成P300潜伏期和波幅测试的502例(82.2%)纳入Meta 分析。发现抗精神病药物治疗与P300波幅微小但显著的增加有关(PSES=0.39, 95% CI [0.26, 0.51], z=6.14, p<0.001)及P300潜伏期微小但显著的减少有关(PSES= -0.29, 95% CI [-0.51, -0.07]; z=2.58; p=0.010)。无显著的发表偏移。结论既往西方的Meta分析主要是基于横断面研究,与此不同,中国的这一精神分裂症患者治疗随访研究的Meta分析发现P300波幅和潜伏期均随药物治疗而改变。提示P300成分,特别是P300波幅,可能是精神分裂症患者药物治疗期间监测认知功能变化的有价值的生物学标记。

听觉中潜伏期诱发电位与人工耳蜗植入

人工耳蜗植入后听力及言语能力恢复与中枢听皮质功能密切相关,听觉中潜伏期诱发电位可反映中枢初级听觉皮层的功能状态。本文综述了听觉中潜伏期诱发电位的起源,声刺激和电刺激,测试方法,影响因素以及临床意义,并讨论其与人工耳蜗植入的相关关系。

听觉诱发中潜伏期反应研究进展

听觉诱发中潜伏期反应（middle latency response,MLR）是较早发现的听觉诱发电位（auditory evoked potential,AEP）成分,常用于中枢听觉通路的功能评估。通过研究MLR的主要成分,可以了解MLR的参数、形态、起源、作用和应用范围,进一步探讨其与听觉通路生理变化的关系,并可以检测中枢神经病变和功能改变。

Sexual function of premature ejaculation patients assayed with Chinese Index of Premature Ejaculation

Aim: To assess the psychometric properties of the Chinese Index of Premature Ejaculation (CIPE). Methods: The sexual function of 167 patients with and 114 normai controls without premature ejaculation (PE) were evaluated with CIPE. All subjects were married and had regular sexual activity. The CIPE has 10 questions, focusing on libido, erectile function, ejaculatory latency, sexual satisfaction and difficulty in delaying ejaculation, self-confi dence and depression. Each question was responded to on a 5 point Likert-type scale. The individual question score and the total scale score were analyzed between the two groups. Results: There were no significant differences between the age, duration of marriage and educational level (P > 0.05) of patients with and vvithout PE and normai controls. The mean latency of patients with PE and normai controls were 1.6±1.2 and 10.2±9.5 minutes, respectively. Significant differences between patients with (26.7±4.6) PE and normai controls (41.9±4.0) were observed on the total score of CIPE (P < 0.01). Using binary logistic regression analysis, PE was significantly related to five questions of the original measure. They are the so-called the CIPE-5 and include: ejaculatory latency, sexual satisfaction of patients and sexual partner, difficulty in delaying ejaculation, anxiety and depression. Receiver Operat ing Characteristic (ROC) curve analysis of CIPE-5 questionnaire indicated that the sensitivity and specificity of CIPE were 97.60 % and 94.74 %, respectively. Employing the total score of CIPE-5, patients with PE could be divided into three groups: mild (>15 point) 19.8 %, moderate (10-14 point) 62.8 % and severe (< 9 point) 16.7 %. Conclusion: The CIPE-5 is a useful method for the evaluation of sexual function of patients with PE and can be used as a clinical endpoint for clinical trials studying the efficacy of pharmacologica] intervention.

Electro-acupuncture Combined with Transcranial Magnetic Stimulation Improves Learning and Memory Function of Rats with Cerebral Infarction by Inhibiting Neuron Cell Apoptosis

This study examined the effect of electro-acupuncture (EA) combined with transcranial magnetic stimulation (TMS) therapy at different time windows on learning and memory ability of rats with cerebral infarction and the underlying mechanism.Two hundred SD rats were randomly divided into four groups:normal group,sham-operated group,model group and EA+TMS group,and each group was then divided into five sub-groups in terms of the different time to start treatment post operation:6,12,24,48 and 72 h.Cerebral infarction models were established in the model and the EA+TMS groups by left middle cerebral artery occlusion/reperfusion (MCAO/R).After treatment for 14 d,the Morris water maze test was applied to examine the spatial learning and memory abilities of rats.In infarcted area,the expression of caspase-3 was immunohistochemically detected,and real-time fluorescent quantitative PCR was used to measure the expression of Bcl-2 mRNA.The results showed that in EA+TMS group compared with model group at the same treatment time windows,the escape latency was substantially shortened,the expression of caspase-3 was considerably decreased and the expression level of Bcl-2 mRNA significantly increased (P<0.05).In the EA+TMS sub-groups,the escape latency was shortest,the expression level of caspase-3 lowest,and the expression level of Bcl-2 mRNA highest at the treatment time window of 24 h.It was concluded that EA combined with TMS can promote neurological function of rats with cerebral infarction by increasing the expression level of Bcl-2 mRNA and decreasing the expression of caspase-3.The best time window is 24 h after perfusion treatment to ischemia.

Deep Reinforcement Learning Based Joint Edge Resource Management in Maritime Network

Due to the rapid development of the maritime networks, there has been a growing demand for computation-intensive applications which have various energy consumption, transmission bandwidth and computing latency requirements. Mobile edge computing(MEC) can efficiently minimize computational latency by offloading computation tasks by the terrestrial access network. In this work, we introduce a space-air-ground-sea integrated network architecture with edge and cloud computing components to provide flexible hybrid computing service for maritime service. In the integrated network, satellites and unmanned aerial vehicles(UAVs) provide the users with edge computing services and network access. Based on the architecture, the joint communication and computation resource allocation problem is modelled as a complex decision process, and a deep reinforcement learning based solution is designed to solve the complex optimization problem. Finally, numerical results verify that the proposed approach can improve the communication and computing efficiency greatly.

Prototype for 5G New Air Interface Technology SCMA and Performance Evaluation

Sparse code multiple access(SCMA) is a novel non-orthogonal multiple access scheme proposed to meet the challenging demand of the future 5G communications, especially in support of the massive connections. The coded bits from each data stream will be directly mapped as multi-dimensional SCMA codeword in complex domain and then spread onto the physical resource elements in a sparse manner. The number of codewords that can be nonorthogonally multiplexed in one SCMA block can be made much larger than the number of orthogonal resource elements therein, resulting in an overloaded system. The sparsity in the spreading pattern and the design in the multidimensional modulator jointly ensure the SCMA codewords can be robustly decoded with low complexity. In this paper, we focus on the low complexity receiver design and verified the superior of an SCMA system via simulations and real-time prototyping. Lab tests and field tests all show that SCMA is a promising candidate for 5G non-orthogonal multiple access which can provide up to 300% overloading that triples the whole system throughput while still enjoying the link performance close to orthogonal transmissions.

Fhyroid hormone controls the gene expression of HSV-1 .AT and ICPO in neuronal cells

Various factors/pathways including hormonal regulation have been suggested to control herpes simplex virus type 1 （HSV-1） latency and reactivation. Our computer analysis identified a DNA repeat containing thyroid hormoneresponsive elements （TRE） in the regulatory region of HSV-1 latency-associated transcript （LAT）. Thyroid hormone （triiodothyronine, T3） functions via its receptor TR （thyroid hormone receptor）, a transcription factor. Present study investigated the roles of TR and T3 in HSV-1 gene expression using cultured neuoroblastoma cell lines. We demonstrated that liganded TR activated LAT transcription, but repressed infected cell protein no. 0 （ICP0） transcription in the presence of LAT TRE. Chromatin immunoprecipitation （CHIP） assays showed that TRs were recruited to LAT TREs independently of T3 and hyperacetylated H4 was associated with the LAT promoter that was transcriptionally active. In addition, ChIP results showed that the chromatin insulator protein CCCTC-binding factor was enriched at the LAT TREs in the presence of TR and T3. In addition, the BRG1 chromatin remodeling complex is found to participate in the T3/TR-mediated LAT activation since overexpression of BRG1 enhanced the LAT transcription and the dominant-negative mutant K785R abolished the activation. This is the first report revealing that TR elicits epigenetic regulation on HSV-1 ICP0 expression in neuronal cells and could have a role in the complex processes of HSV-1 latency/reactivation.